The importance of the Global Positioning System (GPS) and related electronic systems continues to increase in a range of environmental, engineering and navigation applications. However, civilian GPS signals are vulnerable to Radio Frequency (RF) interference. Spoofing is an intentional intervention that aims to force a GPS receiver to acquire and track invalid navigation data. Analysis of spoofing and authentic signal patterns represents the differences as phase, energy and imaginary components of the signal. In this paper, early-late phase, delta, and signal level as the three main features are extracted from the correlation output of the tracking loop. Using these features, spoofing detection can be performed by exploiting conventional machine learning algorithms such as K-Nearest Neighbourhood (KNN) and naive Bayesian classifier. A Neural Network (NN) as a learning machine is a modern computational method for collecting the required knowledge and predicting the output values in complicated systems. This paper presents a new approach for GPS spoofing detection based on multi-layer NN whose inputs are indices of features. Simulation results on a software GPS receiver showed adequate detection accuracy was obtained from NN with a short detection time.

No abstract

The Global Positioning System (GPS) has become widespread in many civilian applications. GPS signals are vulnerable to interference and even low-power interference can easily spoof GPS receivers. In this paper, two techniques are proposed based on correlators and adaptive filtering to diminish the effect of spoofing on GPS-based positioning. The suggested algorithms are implemented in the tracking loop of the receiver. As a first method, a high-resolution correlator is utilised to avoid big parts of the influence of interference. To improve the results, a multicorrelator technique is also employed. In the second method, an adaptive filter is used for estimating the parameters of authentic plus spoof signals. Interference elimination is performed by subtracting the estimated conflict effects from the measured correlation function. These techniques provide easy-to-implement quality assurance tools for anti-spoofing. As a primary step, in this article, the proposed algorithms have been implemented in a Software Receiver (SR) to prove the concept of idea in multipath-free environments. K E Y WO R D S1. Anti-Spoofing.2. Adaptive filters. 3. Correlator. 4. Tracking loop.

The growing dependence of critical civil infrastructure on global positioning system (GPS) makes GPS interference not only a safety threat, but also a matter of national security. The research done in this paper is initiated by the need to diminish this trouble on GPS based positioning. The suggested compensation technique assumes that the presence of a spoofing signal is immediately determined. The position residuals of the last authentic and new fake signals are passed to the wavelet transform (WT). We utilized WT for de-noising. Afterwards, position deviations due to an attack can be extracted and then the estimated position of the received signal will be corrected. As a primary step, the proposed algorithm has been implemented in a stationary software GPS receiver to prove the concept of the idea. The performance of the technique is validated using several laboratory and measurement data sets. Interference mitigation having tolerance of 3% and average of 99.5% is yielded on laboratory data set and complete compensation is achieved on measurement data set. The test results show that the proposed technique supremely gain strength the reliability of civil stationary GPS receiver against interference.

No abstract